Cities are dynamic systems; consist of physical and social networks which interact each other constantly. In this age, an emergent term: Big Data -which is generated with activities that are taken shape in cities integrated with information technologies- provides wide range of inputs for analysing relational structure of cities and uncovering behavioural patterns of city users. This study, searches for methods to develop urban strategies based on the feedback relationship between city's physical and social networks, by considering the data generated from Location Based Social Networks (LBSNs) - that becomes a significant part of daily life as a result of rapidly-developing technologies - together with the outcomes of space syntax analyses. In the case study of the research, for the center Kadikoy region, analyses are held in 3 sequential steps: 1) Acquiring crowdsourced data that users generated in location-based social networks and helding the density analyses in GIS. 2) Helding the space syntax analyses for urban physical network for the study area. 3) Superposing the outcomes in GIS to analyse relationships between the density of urban activity areas and topological characteristics of the physical networks in the study area. In the case study, by considering results of the analyses, making predictions for expansion trends and developing urban strategies compatible with expansion trends of Kadikoy center, are targeted.